Welcome to Inside Active, a podcast about active managers that goes beyond sound bites and headlines and looks deeper into their processes, challenges and philosophies and security selection. I'm David Cohne, i lead mutual fund and active Research at Bloomberg Intelligence. Today, my cost is Christopher Kine, us quantitative strategist at Bloomberg Intelligence. Chris, thank you for joining me today.
Thank you so much for having me. David.
So, you wrote interesting note last month on quality stocks trading near their most expensive levels over the past twenty five years. Is that still the case?
Yes, it is still the case. I mean quality has been certainly the most expensive factor from a historical perspective. Now for a while. You know, our bi quality we keep it pretty simple and we just consider profitability metrics like r O E ro see as well as low leverage. So you know, when you look at the top Quintown on the Russell one thousand is trading over four and a half time sales versus just over one time sales
for the lowest, lowest stock quality Quintal. So that's about over three and a half times more expensive, which is one of the most expensive readings we've seen. I will say also, though, that you know, the profitability of these stocks, of these high quality stocks are much elevated compared to history. Obviously high profitability will you know, high quality will always
have higher profitability. But when you look at the spread between the probitability of low and high quality right now, it's very wide, So you would think there is some fundamental support though the valuations are very stretched.
Great, well, I'm sure today's guest has a great take on valuations. And without further ado, i'd like to welcome Sid Jane to the podcast. Sid is deputy portfolio manager at GQG Partners. Sid, thank you for joining us today.
Thanks for having me on. Guys.
So I have to start with the research note your firm recently published. You know, I couldn't I really think that's the best way to start. So you put out a note called dot com on Steroids. In the note, you know, your firm says that today's market, you know, could actually be worse than the dot com bubble, and your firm argues that, you know, many of today's big tech names represent backward looking quality, not forward with looking quality.
So you know, my question is, you know, what are the clearest quantifiable metrics, say canaries in the coal mine, that in your view, distinguished one from the other.
Yeah.
Absolutely, And I think to kick things off, it's important to understand some of our history with the technology sector where we're not perma bears by any means. We've been actually quite bullish and constructive on the sector for better part of our firm's history.
Of the past decade.
What has caused us to get nervous is this new investment cycle that you're seeing. And if you study again history, when you see major spikes in CAPEX and this is on present level of investment you're seeing right now, that usually tends put poorly for forward looking equity returns. And so that's one metric where it's spiking CAPEX. And you've seen this in the past, whether it's the railroad boom,
electricity boom, internet boom twenty five years ago. That gives us pause, especially when there's really no clear evidence of an ROI on the trillions of dollars investment that are being debated today. The second thing that keeps us nervous is just decelerating revenue growth. These companies, big tech companies were growing twenty thirty percent like Clockwork pre COVID, whereas now we believe the growth runaway is significantly less than
what existed before. I mean, digital ad penetration is now running at seventy percent of over advertising. The metas Googles of the world cannot go twenty thirty percent sustainably anymore. I mean, same with Amazon's Microsoft. They're all slowing down structurally. And so the combination of well of names, high multiples and growth decelerating has problems been all over it. And
last thing I'll say is the accounting shenanigans. And this is a little bit less quantifiable, but it was a lot of press that I'm sure you guys have read about. I mean, the circular vendor financing that you're seeing between Nvidia and open Ai, or today's AMD deal that usually comes at the very end of a cycle. So these are some of the data points that causes to believe that the best years are over for vast majority the technology space. Part to be a large cap the AI winner, so to speak.
Interesting, very interesting. So you're talking about slowing growth, you know, I was wondering, you know, quality of all the factors, you know, tends to have the highest variance if you will, of factor definitions, you know, because you know it's not maybe as straightforward as a value or momentum. So do you have explicit growth elements in your quality factor? I've seen some quants do that, some not. Do you have that component in your quality factor? Yeah?
So growth, we like growing companies.
We don't generally buy companies that are in secular decline. But growth in and of itself is not what we're looking for. That's the only variable that matters. And so the way we think about investing is we want to compound it roughly ten percent annually, and we get there through a function of earnings per share growth plus dividend yield.
That combination gets you there. And so we're equally comfortable owning software companies that get you to that tot re turn predominantly from the growth side, as well as energy companies where there's a much growth but you're getting a massive buyback and dividend return, and we're equally comfortable flexing both sides of that lever So it doesn't just have to be.
Growth awesome, thank you.
So I know, I know you know with your firm, you know it's a big approach with durable earnings rather than you know, typical growth or value labels. How do you, I guess, distinguish between durable earnings from just optimistic growth assumptions.
So I think one area where we'd have maybe have a bit of a differential view is truly appreciate long term capital cycles. And this goes back to our founder in Cio Rajiev having a thirty year track record investing in developed markets, emerging markets, and everything in between. And once you've seen enough cycle that forced you to appreciate that everything experience goes through this. I mean, have you
wrote a white paper action on the semiconductor sector. I think it was back in twenty seventeen House saying this has become the new growth sector and we've got a lot of pushback saying, how can you say that semic corectors haven't.
Grown in ages?
And so you do see those and I think, for example, if you look at today, we believe a lot of the technology sectors are very late cycle. The growth is slowing down, and the addressable market is just a lot less than it used to be. Is on going from twenty thirty percent revenue growth to ten percent, that's problematic We're also very focused on the rate of change of growth. So it's not just is it growing twenty percent a year,
but what direction is that heading? And that goes to our definition of forward looking quality, is accelerating or decelerating, and so that's a much bigger focus of our process. So if you look at the energy space, we are one of the few quality managers that made a large
pivot into energy back in twenty twenty one. Where people have thought this was secular decline, our view was that's the top of a cycle where you've seen most of the industries underwater, not making much money, massive under investment, and that will normalize. And that's how we think about that in terms of the longer term cycle. That's a big portion of how we deploy capital.
So, you know, you mentioned, you know quality. Obviously, one of the funds I really wanted to kind of focus in is the gqg US Quality Value Fund ticker gq ep X, And so you know, if you look at the description, you know, invest in high quality companies with attractively priced future growth products. How does this fund different process or constraints from you know, your broader quality durable earning philosophy.
Yeah, sure. So there's.
The investible The universe of names we choose from is actually the exact same. So every name that we will own on the value strategy has to meet our definition of forward looking quality. So story that's improving has barriers to enter, a strong cashoder, turner, equity and all of that large chat focused. So that's the same. What is different is where the returns are coming from. So, as I mentioned, we go we want to get high single digit load double edit total return with earnings, growth and
dividend yield. The growth strategy can go anywhere in between. The value strategy will focus on the companies that pay the yield. It's so usually the lower multiple names within our investible universe, with a much greater focus on dividend yield. So if you think from a scale of one to ten, one being deep value, ten being super fast growth or growth strategy will usually grow go anywhere between a three to seven on that spectrum, the value strategy will be
between a three to five. Such a smaller subsector over quality universe, and sometimes the strategy looked exactly the same because the growth strategy can go everywhere in between.
I would love to hear about You kind of alluded to this a bit in your last answer, but you know, I would love to hear about what's systematic, what's discretionary, and how that process kind of weaves in together. You know, I talked to a lot of clients that want to do quant but maybe they don't want to do it in a completely systematic way, right, they want to use
their own discretion. So is it like you have, you know, a universe that's filtered for you quantitatively and then you do more research on it, or how does that process work.
It's a great question.
At the end of the day, we will always be a discretionary shop. We are fundamental Bondo stock managers, but we believe heavily in using quant as almost like guardrails on the process. So we have a team of quant analysts and they help monitor things as factor exposures, what factors are working, whatnot, doing historical back testing, making sure
we're not making any obvious mistakes. So, for example, one thing we look at is what factor works in each country, and it's not the same fact that it's work across the world. So for example, if you look at China, one factor that has proven pretty effective longer term is divid and yield, and so our viob is let's maximize the odds as much as we can and focus on companies that have a yield versus purely growth. Now we can buy growthy names, but the job is to just improve the odds.
As much as you can.
As I mentioned the capex, we back to sectors that are seeing significant CAPEX increases generally tend to underperform, and so we monitor as those factors. But at the end of the day, we are a bottom up shop. It's another tool in our toolkit.
Awesome, thank you so much. I would guess it's a similar, you know answer, But as I kind of mentioned previously, like quality definitely has the biggest variance of any quant factor, and I've seen quants have wildly different definitions, and I always ask, like, how do you weight the components of your quality factor? Like, typically I see profitability as probably the main thing, but obviously other things like margins and
stability of fundamentals and all this kind of stuff. So like, is the waiting that you give to each of those is that going to change kind of based on the environment we're in, or do you have some kind of structure in your mind of the weighting of the different components.
So there's a couple of things that change. One is the market environment also does matter. So for example, the pre COVID era, we were much more focused on growth, revenue growth. When it's a zero interest rate world where you're struggling to get economic growth, earnings growth in most major sectors, we are willing to pay a premium for the fastest growing, best companies, whereas today it's a bit murkier.
It's a much higher interest rate world. You have to be more valuation sensitive, and we do think there's a lot of earnings risks from.
The higher revenue growth names. But that's number one.
Number two, and this might be even more important, is that we look at all the same factors that you mentioned in profitability, margins, et cetera. But we are much more focused on rate of change, the second derivative of those factors. As you mentioned the beginning, some of these quality companies today have very strong profits, strong returns today, but the question is next five year do they mean revert,
which is what we think that will start happening. That's much less attractive than a company or a sector that is at the trophy of a cycle. Maybe improving take energy a few years ago, utilities over the past twelve to twenty four months, which you're much more positive on. And so that rate of change is what I think is differentiates us versus many other quality oriented fundamental managers out there.
Awesome. I guess my last question here is what about other factors, Like we talked about value, we talked about quality, like does price momentum matter at all, does low risk matter at all, or any other factors that kind of add into your process.
So I think historically, if you go back, one of the factors, and this is an output not an input, is that we do tend to have a bit of a momentum overlay on our strategies. And the reason for that is a fundamental reason is we like to buy improving stories, not getcheries. So that typically correlates with strong price momentum as well, and so it's rare. We want to be aware which sectors are seeing strong price momentum and not and understanding what is a fundamental reason for that.
We don't have to buy based on just great price action, but if a stock is clearly breaking down, we want to know why because we focus on the largest companies in the world. Is a hyper efficient market, and we have deep respect for price section and that it has been longer term guardrails to our process making sure we're not a stock goes down twenty you buy it looks cheap because another twenty buy it and the classic value trapped territory. So price pomentum does matter to us.
So your research process integrates not just traditional analysis, but also incorporates, you know, journalists, domain experts, others. Can you share an example of, you know where a non traditional perspective may have shifted your investment view.
Absolutely, and it's the non traditional team that truly has some of the most differentiated views on our investment team. Where these are folks who have previously worked as investigated journals, journalists. There's the Wall Street journal or Barons or so Reuters, and they approached the world very differently. They're not actually allowed to talk to the investment team the traditional side. They're working in a vacuum. They don't read seal side research.
They actually go on the ground and talk to people, whether it's former employees, regulators and things of that sort. And they've been a couple of examples where it's helped avoid blow ups but also find incredibly attractive opportunities.
So I'll give a few.
One would have been the technology sector. Actually, back in twenty twenty one, as I mentioned earlier, we made a large pivot from IT tech to energy, which paid out well in twenty twenty two. One of the interesting data points we found was the non traditional team had been talking to a lot of recruiters in Silicon Valley and the feedback they started hearing by summer twenty twenty one, where job offers were getting yanked. You're seeing reduced hiring
across the board. And that was surprising because at that point you might remember, the technology companies were talking about growth, very strong growth into perpetuity revenue, strong, business outlooks strong, but quietly.
They weren't hiring people anymore.
And so when you see in disconnects like that, that cast your attention. Now, that's not the only data point we looked at, but that helped fit this mosaic that maybe things aren't all hunky dory the way people thought they were back in twenty twenty one. Another example would be on the emerging market side. We did a lot of work a few years ago on a coffee company called luckin Coffee in China, which maybe I remember it was a very hot IPO, supposed to be the next
star Books of China. Our non traditional team did a lot of work and they were able to find core filings that show the founder at a criminal track record, obviously was not being talked about on the prospectus, and we were able to avoid that company ended up becoming a fraud a few years later. And so we've seen it add a lot of value in terms of truly differentiated insights versus what you read from Wall Street, the echo chamber of Wall Street.
That's interesting about Luck And I remember that IPO that was a hot IPO. I didn't realize it was a fraud. Wow, good good job avoiding that one. I would love to hear about like stock waiting schemes, you know, is it just like weight? Is there a discretion amount of waiting? Is there like a quant process like a Marcowitz type situation? How do you think about waiting your stocks?
So we've the camp of hold all your eggs in one basket and watch it closely. So typically the top ten names can be roughly fifty percent of our strategy. Top twenty seventy percent and the biggest name will be ten percent for context, and so we do like to run a concentrated strategy, and.
The way we think about it is almost from.
A credit perspective or a credit mindset, where it's not about find the names that have the most raw upside, it's find the names where it can lose.
The least amount of money in.
And so a name could have three hundred percent upside, but if you're wrong, you lose fifty percent. That deserves a spat on the portfolio. But we wouldn't make it a ten percent position. So the quality of the business plays a huge role in terms of how we size these bets. The second thing is also we're focused on very large liquid names because we do change our minds a lot, and that's what's kept us in the game
over the long run. Where the beauty about the process here is it's a super lean team, very fast decision making, and so the moment we see the earnings deteriorate, we can sell out a large position overnight. There's no investment committee, there's no deck you have to put together, and so that really is a risk management process is cutting back losses when the markets move against you materially, earnings are deteriorating,
or there's a macro risk potentially looming. And I think the historical context for that is when you think of Ragie's early career, I mean, starting off in the nineties as an em manager, you're forced to risk management is deeply ingrained in the DNA, and so that's what still plays a role. So there's not a stop loss mechanism or anything like that, use of much faster, quick when you see fundamentals even marginally deteriorate.
That's so interesting. Yeah, you kind of mentioned like using price momentum as a bit of a risk management to whenounce. You kind of got ahead of me on my next question, which was like about risk management. So basically, it's not a systematic process. It's not a stop loss in the market.
You assess the market, you assess you know, your view of earnings or the price momentum or something, and then you can quickly make decision to pull the plug per se, with no investment meetings or investment committees or anything like that exactly.
And in our first gut reaction, when a name moves maturely against the frankly, is that we're wrong until proven otherwise.
A lot of managers like.
To view the in terms of a stall goes down twenty percent, you should buy more and more attractively priced, which is true in theory, but that also assumes that the fundamentals haven't changed at all. The reality of large gap investing today, it's so efficient that generally speaking, when I stop gaps on twenty percent, don you something is fundamentally changed, And it could be the other way around as well. Sawcolls are twenty thirty percent large care well covered.
Something's happened, and you better understand why.
I totally agree.
So I want to go back to valuation just a little bit. You know, if you have a situation where there's a very high quality company but it's trading at a less than ideal valuation, how do you look at it, you know, you know, in terms of you know, waiting, you know, risking the opportunity gets away, or kind of going into it at what you may not consider an ideal valuation.
Yeah, So I think the a couple of things. One is that we actually urge all the.
Investment team members to look at valuation last when it comes to the analysis. The reason for that is if you start, let's say I tell you to look at Into Surgical for example, it's a high quality robotics company. This name trad is that generally fifty to seventy times earning is always super expensive. If you start with valuation first, it makes it, it doesn't. You need to first understand the business, the long term growth runway, the barriers to entry,
and then you can value it. So it's a timing thing we would urge everyone to do. Second is you need to have conviction in the long term runway and the barriers. And when we like to say that the air gets very thin at the top of the mountain, you can't have any misses.
We're fine paying up and we paid.
We've owned companies in the past trading at sixty seventy times revenue in the past rarely, but it does happen. You have to have conviction of the earning trajectory and there's no room for error. You also have to have conviction that the street is missing something. Where this is a high multiple name that street expects to grow a twenty percent a year, but you think it's a thirty
percent grower. That's extremely interesting. The vice versa is not where stream expects thirty percent, you think it's will be twenty percent. So again, the rate of change and the disconnect versus market expectation matters a lot, especially when it's such a high multiple name you have no room brearer.
Last thing I'll say is that there's an opportunity cost element where there's a lot of big world out there, what is what is the opportunity on Maybe there's another sector, another company that's more interesting, that's more attractively valued, which is why I said earlier where pre COVID we felt much more comfortable paying up for growth because there weren't
a million options out there. Today, the investible universe, whether it's from a country perspective, you look at emerging markets or Europe, it's much broader than it's been for in a very long time, and so we feel less the need to chase high multiple names today.
Okay, and we just got one more question, and this kind of a second waiting question. You know, the US equity Value fund is a US quality value fund, is non diversified, so you know it's it's typically going to be more concentrated than some of the more diversified funds. How do you know, just look at position sizing in terms of concentration and you know balancing risk reward trade offs of fewer names.
So our view is you have to make big bets. That's the reason for active management. We do not believe in Benchamarhaggey. We are completely benchmark agnostic, and you can see by our tech positioning where it's gone from seventy percent tech to zero, back to seventy and everything in between. But the caveat is when you're making these big bets, you do have to have a deep respect for price
action and selling quickly when the fundamentals are deteriorating. The easiest way to blow up is you have a large position. That's the fundamentals are getting worse and you don't cut back risk immediately, which is why if you look at our turnover, it's typically north of fifty percent, which is quite high for a long only manager.
And then that is part of the risk manage element.
We also believe in macro in terms of a risk off tool.
We are a bottom up shop.
We won't buy a name because of a good macro setup, but if we feel there's a clear macro risk pending, we'll cut back risk aggressively.
And this goes back to again Rodger being an EA.
Manager hard back in the thirties and in the nineties and then so a class example would be back in twenty twenty one twenty twenty two, where the mistake a lot of quality managers missed made was not appreciating macro where what is the impact of higher rates, higher inflation on tech valuations. That was a fundamental issue that many quality managers missed. But our view was the macro. Respect
for macros helped us preserve capital in bear markets. So these are some of the things that play a role in terms of how we size bets, how risk on we are at any given moment and not that makes sense.
Well, unfortunately we have to end here, but this is a great conversation. Thank you so much said for.
Joining us shoe the time. Guys, thanks again, thank you.
And Chris, thanks again for being my host. Thank you, and I want to thank our listeners. If you liked the episode, please subscribe and leave a review. Also, if you'd like to see more of our research, go to bi fund go for fun research and b I S t o X go for stock research on the Bloomberg terminal until our next episode. This is David Cone with Inside Active